OP0293 PHOTOREALISTIC DEPICTION OF RHEUMATIC PATHOLOGIES BY CINEMATIC RENDERING FACILITATES DISEASE UNDERSTANDING OF PATIENTS WITH RHEUMATIC DISEASES
Authors: M. Pachowsky, H. Morf, D. Simon, V. Schönau, L. Valor, J. Knitza, K. Engel, M. Uder, A. Hueber, G. Schett, A. Kleyer
Journal: Annals of the Rheumatic Diseases (2022)

Background Treatment success of a rheumatic disease crucially depends on whether a patient is sufficiently informed about the disease[1]. Visual methods are suitable for explaining diseases[2]. Cinematic rendering (CR) is a new method that allows to segment standard medical images into images that illustrate disease pathologies in a photorealistic way. As such, CR provides new opportunities to visualize diseases and but could therefore be a valuable tool for patients with rheumatic and musculoskeletal disease (RMD).[3] Objectives We questioned, if it is possible to apply CR on images from structural lesions of patients with rheumatoid arthritis (RA), Psoriatic Arthritis (PsA) and axial Spondyloarthritis (axSpA) and to test whether such images are helpful to patients with RMDs to understand their disease process. application in doctor-patient communication. Methods We selected conventional computed tomography (CT) and high-resolution peripheral CT (HR-pQCT) from patients with rheumatoid arthritis (RA), Psoriatic Arthritis (PsA) and axial Spondyloarthritis (axSpA) that showed typical changes of the respective disease. HR-pQCT measurements were performed in RA and PsA at the Rheumatology Department. CT Measurements of the spine in an axSpA patient was provided from AH. All images were segmented to CR images using a prototype software by the manufacturer Siemens Healthineers. In a prospective study on consecutive patients with RA, PsA, axSpA these images were used to explain the depicted pathognomonic pathologies and compared to conventional imaging in a structured doctor-patient interview. In the last step, patients filled in a quantitative questionnaire (Likert Scale 1-5) about their perspectives answering following questions: Did you understand your disease in the provided Cinematic Rendering images? Did you understand your disease better through the presentation using Cinematic Rendering images than with a normal X-ray image? Do you think it would be reasonable to use this type of Cinematic Rendering to improve patients’ understanding of their disease? Descriptive statistical methods were used. Results CR images of rheumatic diseases were successfully generated from above mentioned imaging data (CT, HR-pQCT). Bone erosions, osteophytes, enthesiophytes, osteoporosis and ankylosis of the spine could be visualized in photorealistic detail. Figure 1 shows examples of a images of a patient with RA and axSpA with typical bone changes. 65 patients (23 RA/23 PsA/19 axSpA; f 55%) were guided through CR images of their respective disease by an experienced rheumatologist, followed by completing the questionnaire mentioned above. Patients stated that CR was very helpful to understand their disease process (4.39±0.15), that understanding diseases by CR was better than the one obtained by conventional radiographs (4.43±0.20) and that they considered such technology helpful for improving disease understanding (4.35±0.09). Conclusion CR seems to be a promising teaching tool for RMD patients facilitating an improved understanding of their disease process and in consequence my also improve adherence of RMD patients to their anti-rheumatic treatment. References [1]Ritschl, V., et al., 2020 EULAR points to consider for the prevention, screening, assessment and management of non-adherence to treatment in people with rheumatic and musculoskeletal diseases for use in clinical practice. Ann Rheum Dis, 2020. [2]Kleyer, A., et al., Development of three-dimensional prints of arthritic joints for supporting patients’ awareness to structural damage. Arthritis Res Ther, 2017. 19 (1): p. 34. [3]Berger, F., et al., Application of Cinematic Rendering in Clinical Routine CT Examination of Ankle Sprains. AJR Am J Roentgenol, 2018. 211 (4): p. 887-890. Acknowledgements Siemens Healthineers /Dr.Klaus Engel for providing CR expertise Disclosure of Interests None declared